Direct response and feedback system

ABSTRACT

The invention provides methods and systems for analyzing and routing items in a social media stream.

CROSS-REFERENCE TO RELATED APPLICATION Claim of Priority

This application is related to and claims priority U.S. patentapplication Ser. No. 13/135,929 entitled DIRECT RESPONSE AND FEEDBACKSYSTEM which was filed on Jul. 19, 2011, which is related to and claimspriority to U.S. Patent Application No. 61/365,465 entitled DIRECTRESPONSE AND FEEDBACK SYSTEM which was filed on Jul. 19, 2010, whichboth name at least Babar Bhatti as a common inventor.

FIELD OF THE INVENTION

This invention relates generally to monitoring social media commentary.

Problem Statement Interpretation Considerations

This section describes the technical field in more detail, and discussesproblems encountered in the technical field. This section does notdescribe prior art as defined for purposes of anticipation orobviousness under 35 U.S.C. section 102 or 35 U.S.C. section 103. Thus,nothing stated in the Problem Statement is to be construed as prior art.

DISCUSSION

Definition: The term “item” herein refers to an individual element oftextual information, such as an email message, a blog post, a messagesent from a cell phone by means of texting, a Twitter message, or anyother specific textual transmission.

Definition: The term “stream” herein refers to an aggregation of items,typically delivered by electronic means.

Definition: The term “person” refers to one or more individuals, who mayalso be analysts within one or more business units.

Definition: The term “recipient” herein refers to a person or personswho receives an item.

Many organizations today have a need to monitor what is being said onthe many forms of social communications media that are available, suchas Twitter messages, blog posts, email messages, or websites. Variouswell-known means exist to provide an organization with this informationin the form of electronic data streams of individual messages or“items.”

Individuals in an organization typically have responsibility fordifferent subject matter areas. It is important for each item to reachan individual in the organization who is adequately prepared to handlethe item. The process of routing items to appropriate individuals withinan organization has historically been a purely manual task, where foreach item, a person decides who should handle the item.

Once an item arrives in the hands of the individual who should handleit, historically that individual makes an appropriate, but purely manualresponse that may include doing nothing, writing and posting a reply tothe appropriate channel, or summarizing and forwarding the processeditems to organizational management. Accordingly, there exists the needfor systems and methods of more efficiently distributing and managingelectronic items.

BRIEF DESCRIPTION OF THE DRAWINGS

Various aspects of the invention, as well as an embodiment, are betterunderstood by reference to the following detailed description. To betterunderstand the invention, the detailed description should be read inconjunction with the drawings and tables, in which:

FIG. 1 illustrates an algorithm according to the teachings of thepresent invention.

DETAILED DESCRIPTION OF THE INVENTION Interpretation Considerations

When reading this section (which describes an exemplary embodiment ofthe best mode of the invention, hereinafter “exemplary embodiment”), oneshould keep in mind several points. First, the following exemplaryembodiment is what the inventor believes to be the best mode forpracticing the invention at the time this patent was filed. Thus, sinceone of ordinary skill in the art may recognize from the followingexemplary embodiment that substantially equivalent structures orsubstantially equivalent acts may be used to achieve the same results inexactly the same way, or to achieve the same results in a not dissimilarway, the following exemplary embodiment should not be interpreted aslimiting the invention to one embodiment.

Likewise, individual aspects (sometimes called species) of the inventionare provided as examples, and, accordingly, one of ordinary skill in theart may recognize from a following exemplary structure (or a followingexemplary act) that a substantially equivalent structure orsubstantially equivalent act may be used to either achieve the sameresults in substantially the same way, or to achieve the same results ina not dissimilar way.

Accordingly, the discussion of a species (or a specific item) invokesthe genus (the class of items) to which that species belongs as well asrelated species in that genus. Likewise, the recitation of a genusinvokes the species known in the art. Furthermore, it is recognized thatas technology develops, a number of additional alternatives to achievean aspect of the invention may arise. Such advances are herebyincorporated within their respective genus, and should be recognized asbeing functionally equivalent or structurally equivalent to the aspectshown or described.

Second, the only essential aspects of the invention are identified bythe claims. Thus, aspects of the invention, including elements, acts,functions, and relationships (shown or described) should not beinterpreted as being essential unless they are explicitly described andidentified as being essential. Third, a function or an act should beinterpreted as incorporating all modes of doing that function or act,unless otherwise explicitly stated (for example, one recognizes that“tacking” may be done by nailing, stapling, gluing, hot gunning,riveting, etc., and so a use of the word tacking invokes stapling,gluing, etc., and all other modes of that word and similar words, suchas “attaching”).

Fourth, unless explicitly stated otherwise, conjunctive words (such as“or”, “and”, “including”, or “comprising” for example) should beinterpreted in the inclusive, not the exclusive, sense. Fifth, the words“means” and “step” are provided to facilitate the reader's understandingof the invention and do not mean “means” or “step” as defined in §112,paragraph 6 of 35 U.S.C., unless used as “means for -functioning-” or“step for -functioning-” in the Claims section. Sixth, the invention isalso described in view of the Festo decisions, and, in that regard, theclaims and the invention incorporate equivalents known, unknown,foreseeable, and unforeseeable. Seventh, the language and each word usedin the invention should be given the ordinary interpretation of thelanguage and the word, unless indicated otherwise.

Some methods of the invention may be practiced by placing the inventionon a computer-readable medium, particularly control anddetection/feedback methodologies. Computer-readable mediums includepassive data storage, such as a random access memory (RAM) as well assemi-permanent data storage. In addition, the invention may be embodiedin the RAM of a computer and effectively transform a standard computerinto a new specific computing machine. Further, computing machines maybe virtual computing machines, and/or “the cloud.”

Data elements are organizations of data. One data element could be asimple electric signal placed on a data cable. One common and moresophisticated data element is called a packet. Other data elements couldinclude packets with additional headers/footers/flags. Data signalscomprise data, and are carried across transmission mediums and store andtransport various data structures, and, thus, may be used to operate themethods of the invention. It should be noted in the following discussionthat acts with like names are performed in like manners, unlessotherwise stated. Of course, the foregoing discussions and definitionsare provided for clarification purposes and are not limiting. Words andphrases are to be given their ordinary plain meaning unless indicatedotherwise. The numerous innovative teachings of present application aredescribed with particular reference to presently preferred embodiments.

DESCRIPTION OF THE DRAWINGS

The invention is a process by which individual textual information itemsfrom a stream can be analyzed to discover trending topics or sentimentsand routed with reference to the item's trending topics or sentiments toa person or persons most appropriate to review the item, who may respondto the author of the item through an appropriate channel. The responsemay include an individual message, a possibly previously preparedgeneric message, and/or a survey link. Each person receiving a routeditem has an option to deal immediately with the item or to forward theitem to a more appropriate person. The process includes a means to learnto improve its routing by reference to the choices made by the person.The process may log activity, generate periodic reports and route thosereports to management. Steps are described to accomplish the acts thataccomplish the process; however, those skilled in the art will recognizethat equivalent steps may exist in each case, and that changing any stepto one of these equivalents does not materially alter the overallprocess.

FIG. 1 illustrates an algorithm according to the teachings of thepresent invention. The algorithm begins with a receipt of an item in anincoming data stream event 10. In the incoming data streams act 10, anorganization preferably obtains a stream or streams of items fromvarious sources, which can include commercial vendors who aggregate andforward such streams, or collection and aggregation means that theorganization develops for itself. From the incoming data stream, thealgorithm segregates individual items in a segregate individual itemsact 12, such as distinct tweets, blogs, or emails. In the segregateindividual items act 12, the data streams are broken into individualitems, if necessary, by exploiting the typical boundaries of eachindividual item, such as end-of-message marks. These segregatedindividual items may also be recorded to an historical database at thistime for further analysis, or at later times, for example in theperiodic report act 32, or in the update knowledge base act 34.

The algorithm then analyzes each item in an analyze each item act 14,and uses the data it discovers to identify trending topics or sentimentsin a discover trending topics or sentiments act 16. In the analyze eachitem act 14, the system preferably updates a histogram with informationfrom an item. The histogram is built from the information contained in aparticular, pre-defined span of time, such as an hour or a day. Thespans of two histograms may overlap or not. The system first determinesthe histogram(s) to which the current item applies, then updates thathistogram(s). To update a histogram, the system first counts how manytimes each distinct word in the item appears in that item and adds thattotal to the count for that word in the histogram, creating a new entryin the histogram if the word has not previously been seen. It thenstores the item and its association with the particular histogram. Thenthe system compares the current time against the definition of the timewindow for the histogram. A ny items older than the oldest valid timefor the histogram are accessed, and their words counts are subtractedfrom the appropriate word entries in the histogram, deleting wordentries from the histogram whose counts have dropped to zero. Common“stop words,” such as “a,” “and,” or “the” may be omitted from thehistogram, if desired. A list of phrases of interest, such as a multiword product name, may be provided to the process, and if provided, theprocess will count the number of instances of these phrases that appearin items within the time window in a separate section of the histogramreserved for phrases. A list of words of interest, which may or may notappear in any item within the time window, may be provided to theprocess, and if provided, the process will count the number of instancesof these words that appear within the time window. The system providesmeans to change these optional lists of phrases or words as desired. Thehistogram so produced is taken to be the definition of trending topicsand sentiments of items for the window of time to which it refers. Thishistogram is known as a “trend histogram.”

In the discover trending topics or sentiments act 16, the systemcompares an item with the current trend histogram from analyze each itemact 14 to determine the trending topics or sentiments of the item. To dothis, the system analyzes the item to produce an “item histogram,” usingthe same procedure followed to produce the trend histogram; however, thesystem produces this item histogram exclusively from the item. Thesystem first expresses the counts in both histograms as fractions bydividing each count in a histogram by the total of the counts in thathistogram. Then the system constructs a composite histogram bymultiplying together the fractions of corresponding histogram entriesand dividing each resulting fraction by the sum of all the resultingfractions. Any histogram entry in either histogram that is not also anentry in the other histogram is omitted. The system may be instructed toexclude any entry in the composite histogram that is smaller than somepredetermined value. If so, the composite histogram is thenre-normalized by dividing each of the fractions of the remaining entriesby the sum of those fractions. The resulting composite histogram is the“trend estimate” for the item.

For each trending topic, the algorithm routes the highest scoring set ofitems, together with the scoring analysis for each item in the set, tothe appropriate persons in the most relevant business groups within thecompany, in a rout items act 18. In the rout items act 18, at apredetermined time interval, the process updates and maintains duringthe interval a “routing list.” Each entry in the routing list consistsof a trend estimate histogram similar in structure to the one producedby the discover trending topics or sentiments act 16, and a list ofpersons who should receive items that match this particular trendestimate histogram. Each of these trend estimate histograms may beproduced by any reasonable means, including by hand or by a processsimilar to the one previously discussed. Each corresponding list ofpersons may likewise be produced by any reasonable means, including byhand or by machine learning techniques such as those described in thelearning act 22. The process compares the trend estimate for each itemagainst this routing list and obtains the routing list entry thatexhibits the best match between the item's trend estimate and the listentry's trend estimate. The system evaluates matches by comparing thetrend estimate of the item with the trend estimate of the routing listentry. To do this, the system constructs a score. The largest resultingscore is evaluated to be the best match. The system constructs the scorefor a particular routing list entry, for example, by multiplying theelements of the trend estimate for the item with the correspondingelements of the trend estimate for the particular entry, and summing theresulting products. The routing list entry that produces the largest sumby this method is the best match. Many appropriate methods to accomplishthis type of scoring are well known, and any of them may be employed.The process then routes the item to the person(s) in the routing tablefor the winning routing list entry.

In a person query 20, if a recipient decides that the item should go toanother person, the algorithm forwards the item to that person, and thealgorithm logs the item in order to learn from this decision to improveits routing in a learning act 22. This can be accomplished via email,text, SMS, MMS, push notifications, or any other appropriate transfermechanism. In the learning act 22, the algorithm is automaticallynotified of all forwarded sets, specifically who sent them and whoreceived them. This information is analyzed using data mining algorithmsto improve future routing by updating the routing list. In oneembodiment, the algorithm develops a probability or measure that the setshould be forwarded to any particular company unit or individual.Preferred techniques include support vectors machines, naïve Bayesianclassifiers, back propagation neural networks, and similar capabilities.Techniques can specifically include a routing list that is partially orentirely created and maintained by human beings. The routing list ispreferably built and maintained to determine who should receiveparticular trending topics or sentiments. Further, the routing portionof this system can take advantage of the routing table.

If the item is not forwarded, the algorithm proceeds to a response query30. In the response query 30, the system provides the opportunity forthe recipient of the item to respond to the originator of the item. Thisis preferably done by providing choices that are familiar to thoseskilled in the art of communications programming to write and send amessage from the recipient to the originator. Such options include suchthings as an Internet form that can be filled out and edited, thencaused to be sent, for example via the Internet email system, from therecipient to the originator, or any other well known and suitablemethod, such as providing posting a reply on a message board that can beviewed by the originator of the item, or by the public at large.

Further in the response query 30, the algorithm provides each recipientwith the opportunity to post a response to each item through a channelchosen by the recipient. The algorithm may provide a means for eachrecipient to include a previously prepared anonymous survey link in anyresponse.

If a response is generated via the response query 30, the algorithmadvances to a include call to action query 24, which enables the user togain more information about a particular item. Preferably, the algorithmprovides the ability for an item's recipient to decide whether or not torespond to the originator of the particular item with a call to action.If the user chooses to issue a call to action the algorithm proceeds toa call to action act 26. The call to action 26 act can be implementedvia the internet. For example, when the recipient clicks on an optionbutton on his or her screen to include a survey link, this action causesa link to the web page that holds a previously prepared, on line surveyto be inserted into the message to be sent to the originator. The surveymay collect data anonymously from survey respondents. The system handlesany other similar and appropriate call to action in a similar fashion. Acall-to-action can allow an organization that uses the subject inventionthe opportunity to measure the effectiveness of their response.

Regardless of the decision to the call to action query 24, the algorithmthen proceeds to a post response act 28 in which a response is posted tothe originator or others. For example, in one embodiment, when therecipient clicks on a “send” button, similar in design and functionalityto those found in many email programs, the response composed by therecipient is caused to be sent to the originator by a suitablemechanism, such as email delivery. The response can be to a single useror a group. It may include one or more delivery mechanisms, such asemail or posting to an on line message board. The group may be an ad hocgroup defined by the recipient at the time of posting a response. Thealgorithm then proceeds to a periodic report act 32.

If no response is generated via the response query 30, the algorithm mayimmediately proceed to generate a management report and sends it tomanagement in the periodic report act 32. In the periodic report act 32the algorithm produces an on-line display, often described as a“dashboard” display to enable inspection of major aspects of the ongoingoperation of the system itself, including the ability to “drill down” todiscover the details of any summarized data item. This management datadisplay can include various types of reports at the direction ofmanagement.

Next, in an update act 34, the algorithm updates a knowledge base bylogging and tracking preferably all activities. In the update act 34,the system collects and stores a cumulative history of all data thatflows through it and all actions taken on that data. Standard datamining tools can then be used by management to analyze any aspect ofhistorical system operation. The preferred algorithm ends with aperiodic report act 36 wherein the knowledge base is analyzed togenerate reports and alerts to management.

We claim:
 1. A method that converts a general computing device into aspecific computing machine for analyzing and routing items, the methodcomprising: receiving from a remote input device a social media datastream comprising at least an item; in a server segregating each itembased on the content of that item; identifying a trending topic orsentiment; scoring each topic and sentiment; and associating a firstpreferred recipient with each topic and sentiment; then routing an itemassociated with a topic or sentiment to the first preferred recipient;and posting a response to the originator of the item in the social mediadata stream.
 2. The method of claim 1 further comprising receiving anindication that the item has been forwarded to another recipient.
 3. Themethod of claim 2 further comprising associating the topic or sentimentwith a second preferred recipient.
 4. The method of claim 2 furthercomprising disassociating the topic or sentiment with the firstpreferred recipient.
 5. The method of claim 1 further comprising sendinga call to action to the originator of the item.
 6. The method of claim 1further comprising generating a management report comprising a dashboarddisplay.
 7. The method of claim 1 further comprising updating aknowledge database.
 8. The method of claim 7 further comprisinggenerating a management report comprising a dashboard display based onthe knowledge base.